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Multi-modal Intent Recognition Method for the Soft Hand Rehabilitation Exoskeleton
Chen WY(陈文远)1,2,3; Yu P(于鹏)1,2; Li GY(李广勇)4; Wang WX(王文学)1,2; Yao C(姚辰)1,2; Liu LQ(刘连庆)1,2
Department机器人学研究室
Conference Name39th Chinese Control Conference, CCC 2020
Conference DateJuly 27-29, 2020
Conference PlaceShenyang, China
Author of SourceSystems Engineering Society of China (SESC) ; Technical Committee on Control Theory (TCCT) of Chinese Association of Automation (CAA)
Source PublicationProceedings of the 39th Chinese Control Conference, CCC 2020
PublisherIEEE Computer Society
Publication PlaceWashington, USA
2020
Pages3789-3794
Indexed ByEI
EI Accession number20203909241916
Contribution Rank1
ISSN1934-1768
ISBN978-9-8815-6390-3
Keywordsoft hand exoskeleton bionics anatomy Conference muti-modal intention recognition method
AbstractStroke has become the second most disabling disease in the world. Due to the intensive demand for physical therapists and the severe dependence on hospitals, the cost for the treatment of stroke patients is huge. As the most flexible limb of the human body, the hand faces more severe challenges, which has a much lower degree of recovery than the upper and lower limbs. In the face of these challenges, a new treatment, exoskeleton-based rehabilitation, has demonstrated new vitality. This paper proposes a novel design of the soft hand exoskeleton based on bionics and anatomy and the exoskeleton could help the users bend and extend their fingers, which would greatly improve the motor ability of stroke patients. Through the control of the six drive motors, the exoskeleton could achieve most of the hand's freedom of training. At the same time, we propose a multi-modal intent recognition method based on machine vision and machine speech. Under specific rehabilitation training scenarios, both healthy subjects and patients could complete grasping tasks in the wearing of the exoskeleton, overcoming potential security risks caused by misidentification due to using the single-modal intent understanding method.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/27702
Collection机器人学研究室
Corresponding AuthorYu P(于鹏); Li GY(李广勇)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
4.Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh
Recommended Citation
GB/T 7714
Chen WY,Yu P,Li GY,et al. Multi-modal Intent Recognition Method for the Soft Hand Rehabilitation Exoskeleton[C]//Systems Engineering Society of China (SESC), Technical Committee on Control Theory (TCCT) of Chinese Association of Automation (CAA). Washington, USA:IEEE Computer Society,2020:3789-3794.
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